Information processing apparatus, information processing method, and program

ABSTRACT

An information processing apparatus that estimates waiting time in a waiting line with improved accuracy includes a first acquisition unit that acquires a number of objects in the waiting line, a second acquisition unit that acquires frequency of an object exiting the waiting line, and an estimation unit that estimates waiting time in the waiting line based on the acquired number of objects in the waiting line and the acquired frequency of an object exiting the waiting line.

BACKGROUND Field

The present disclosure relates to an information processing apparatus,an information processing method, and a program.

Description of the Related Art

There is a system that calculates waiting time from average time takenfor service and the number of waiting people. There is also a systemthat estimates the waiting time from the length of a line and the movingtime of a person in the line.

For example, Japanese Patent Application Laid-Open No. 9-147187discusses a system for informing waiting time with respect to an area atan automatic teller machine (ATM) of a bank. The system calculates thewaiting time of each customer in a waiting line by multiplying apreregistered average transaction time by the number of customersregistered in the waiting line.

Japanese Patent Application Laid-Open No. 2007-317052 discusses a systemthat generates information associated with a waiting line by processinga video image captured by a monitoring camera and calculates waitingtime based on total length of the line.

Japanese Patent No. 5932850 discusses a system that acquires image dataobtained by photographing a line including a plurality of moving bodiesand calculates waiting time in the line from the length of the line anda moving distance of one of the moving bodies.

SUMMARY

According to an aspect of the present disclosure, an informationprocessing apparatus includes a first acquisition unit configured toacquire the number of objects in a waiting line, a second acquisitionunit configured to acquire frequency of an object exiting the waitingline, and an estimation unit configured to estimate waiting time in thewaiting line based on the number of objects in the waiting line acquiredby the first acquisition unit and the frequency of an object exiting thewaiting line acquired by the second acquisition unit.

Further features will become apparent from the following description ofexemplary embodiments with reference to the attached drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B illustrate a hardware configuration of an informationprocessing apparatus as an example.

FIG. 2 is a flowchart illustrating processing of the informationprocessing apparatus as an example.

FIGS. 3A and 3B illustrate application of the waiting time estimationsystem as an example.

FIG. 4 is a result of waiting time estimation processing as an example.

FIG. 5 illustrates a system configuration of a waiting time estimationsystem as an example.

FIG. 6 illustrates a functional configuration of an informationprocessing apparatus as an example.

FIGS. 7A to 7F illustrate application of the waiting time estimationsystem as an example.

FIG. 8 is a result of waiting time estimation processing as an example.

FIG. 9 illustrates application of a waiting time estimation system as anexample.

FIGS. 10A and 10B illustrate areas for counting objects as an example.

FIG. 11 illustrates a system configuration of the waiting timeestimation system as an example.

FIG. 12 illustrates processing timing of the waiting time estimationsystem as an example.

FIGS. 13A and 13B illustrate processing of the waiting time estimationsystem as an example.

DESCRIPTION OF THE EMBODIMENTS

Hereinafter, exemplary embodiments will be described with reference tothe drawings.

A first exemplary embodiment will be described below. In the presentexemplary embodiment, processing in which a waiting time estimationsystem acquires waiting time of a waiting line will be described. In thepresent exemplary embodiment, objects in the waiting line are humanbodies, but can be animals, such as livestock, industrial products orintermediate products carried on a lane of a factory, or cargo orcontainers carried on a conveying lane.

The waiting time estimation system includes an information processingapparatus 100. The information processing apparatus 100 is an apparatusthat acquires the number of objects in the waiting line, and frequencyat which an object passes through an exit of the waiting line (frequencyof an object exiting the waiting line). The information processingapparatus 100 then acquires an estimated value of waiting time of thewaiting line based on the acquired number of objects and the acquiredfrequency. The information processing apparatus 100 includes, forexample, a personal computer (PC), a server apparatus, or a tabletapparatus.

FIG. 1A illustrates a hardware configuration of the informationprocessing apparatus 100 as an example according to the presentexemplary embodiment.

The information processing apparatus 100 includes a memory 110, acentral processing unit (CPU) 111, a communication control unit 112, aninput control unit 113, and a display control unit 114.

The memory 110 is a storage device that stores various programs, varioussetting data, various threshold data, and image data obtained byphotographing a waiting line. The CPU 111 is a central processing unitthat controls processing of the information processing apparatus 100.The communication control unit 112 is a unit used for communication withan external device through a network. The input control unit 113 is aunit that controls input of information to the information processingapparatus 100 through an input apparatus 120. The display control unit114 is a unit that controls display of a screen on a display apparatus130. In the present exemplary embodiment, the information processingapparatus 100 and the display apparatus 130 are independent apparatuses,but the display apparatus 130 can be included in the informationprocessing apparatus 100. The waiting time estimation system can includea plurality of display apparatuses as the display apparatus 130.

The CPU 111 performs relevant processing based on a program stored inthe memory 110 or the like. The CPU 111 realizes functions of theinformation processing apparatus 100 described below with reference toFIG. 1B and the processing of the flowcharts described below withreference to FIG. 2.

FIG. 1B illustrates a functional configuration of the informationprocessing apparatus 100 as an example according to the presentexemplary embodiment.

The information processing apparatus 100 includes a count unit 103, apassage frequency calculation unit 104, a setting unit 105, a waitingtime estimation unit 106, a communication unit 107, and a display unit108.

A first passage detection unit 101 and a second passage detection unit102 detect passage of an object included in the waiting line. The firstpassage detection unit 101 and the second passage detection unit 102 canbe, for example, a passage sensor using infrared radiation, a camerawith an image analysis function for detecting passage of an object basedon captured images, or the like. The first passage detection unit 101 isprovided at an exit of the waiting line and detects an object exitingthe waiting line. The second passage detection unit 102 is provided atan entrance of the waiting line and detects an object entering thewaiting line.

A partial waiting line cut out from a waiting line can also beconsidered as one waiting line. For example, the waiting time estimationsystem can regard a partial waiting line from the center position of onewaiting line to the exit as one waiting line, and acquire waiting timefrom the central position to the exit.

In the present exemplary embodiment, the first passage detection unit101 and the second passage detection unit 102 detect an object enteringthe waiting line and an object exiting the waiting line, and transmitinformation indicating that an object has been detected to the countunit 103 and the passage frequency calculation unit 104. The waitingtime estimation system can include an imaging apparatus, such as acamera, for photographing the entrance and the exit of the waiting linewithout including the first passage detection unit 101 or the secondpassage detection unit 102. In this case, the CPU 111 detects an objectentering the waiting line and an object exiting the waiting line basedon images of the entrance and the exit of the waiting line captured bythe imaging apparatus. In addition, the first passage detection unit 101and the second passage detection unit 102 can change an object to bedetected, for example, based on an instruction from the informationprocessing apparatus 100 based on an operation performed by a userthrough the input apparatus 120.

The count unit 103 acquires the number of objects existing in thewaiting line based on the result of detection of the objects passingthrough the entrance or the exit of the object waiting line by the firstpassage detection unit 101 and the second passage detection unit 102.

The passage frequency calculation unit 104 acquires frequency as firstpassage frequency, of objects passing through the exit of the waitingline within a preset time period, based on at least results of detectionof the objects passing through the exit of the waiting line by the firstpassage detection unit 101. The passage frequency calculation unit 104can calculate the first passage frequency based on the state of thewaiting line or an interval in outputting the waiting time. In addition,the passage frequency calculation unit 104 can acquire frequency assecond passage frequency, of the objects passing through the entrance ofthe waiting line (frequency at which the objects enter the waitingline), based on detection results by the second passage detection unit102.

The setting unit 105 accepts the number of people waiting at the timewhen the waiting time estimation system is activated, and specificationof timing for estimating or displaying the waiting time, based on anoperation of a user through the input apparatus 120. The setting unit105 determines the information indicated by the accepted specificationas setting information that is used for waiting time estimationprocessing. The setting unit 105 can store the acquired information inthe memory 110 or the like. In the case where the setting information isalready stored in the memory 110, the setting unit 105 can use thestored setting information without accepting specification from theuser. This method eliminates the need for a user to perform an inputoperation each time the waiting time estimation system is activated, andthe waiting time estimation system can improve convenience of users.

The waiting time estimation unit 106 performs waiting time estimation ata time of performing the waiting time estimation indicated by thesetting information determined by the setting unit 105 in a followingmanner. That is, based on the number of objects in the waiting lineacquired by the count unit 103 and the first passage frequency acquiredby the passage frequency calculation unit 104, the waiting timeestimation unit 106 acquires a value estimated to be a waiting time ofthe waiting line. The waiting time estimation unit 106 then records theacquired information about the waiting time in the memory 110 or thelike. Alternatively, the waiting time estimation unit 106 can acquirethe waiting time of the waiting line based on the second passagefrequency in addition to the first passage frequency. The communicationunit 107 transmits the information about the waiting time acquired bythe waiting time estimation unit 106 to an external terminal device orthe like. The communication unit 107 performs wired or wirelesscommunication with a device, such as a terminal device.

At the time indicated by the setting information determined by thesetting unit 105, the display unit 108 displays on the display apparatus130 information indicating the waiting time acquired by the waiting timeestimation unit 106, e.g., for example, a character string or numbersequence.

In the present exemplary embodiment, each of the functional components103 to 108 is a functional component included in the informationprocessing apparatus 100 that is a single device. However, within asystem to which a plurality of information processing apparatuses isconnected, the respective functional components 103 to 108 can bedistributed across the plurality of information processing apparatuses.In addition, the respective functional components 103 to 108 can beconfigured as hardware to be included in the information processingapparatus 100.

FIG. 2 is a flowchart illustrating processing of the informationprocessing apparatus 100 according to the first exemplary embodiment asone example.

The processing of FIG. 2 starts, for example, at a time when the waitingtime estimation system is activated.

In step S201, the setting unit 105 acquires setting information used forthe waiting time estimation processing based on the operation of a userthrough the input apparatus 120 or by acquiring the setting informationstored in the memory 110. The count unit 103 initializes the number ofobjects in the waiting line using the number of objects in the waitingline at a time when the waiting time estimation system is activated. Thetime is indicated by the acquired setting information.

In step S202, the first passage detection unit 101 and the secondpassage detection unit 102 detect passage of an object based on signalsfrom the passage sensors included in the first passage detection unit101 and the second passage detection unit 102. The first passagedetection unit 101 is installed near the exit of the waiting line anddetects an object exiting the waiting line. The second passage detectionunit 102 is installed near the entrance of the waiting line and detectsan object entering the waiting line.

In step S203, the count unit 103 acquires the number of objects presentin the waiting line based on the results of the detection processing bythe first passage detection unit 101 and the second passage detectionunit 102.

In step S204, based on the results of the detection processing by thefirst passage detection unit 101, the passage frequency calculation unit104 acquires the frequency of an object that has exited the waiting linewithin a set time period as the first passage frequency. For example, bydividing by the set time period the number of objects that has exitedthe waiting line within the set time period, the passage frequencycalculation unit 104 acquires the number of objects that exit from thewaiting line per unit time period as the first passage frequency. Thepassage frequency calculation unit 104 can store the acquired firstpassage frequency in the memory 110 or the like. The passage frequencycalculation unit 104 can calculate the second passage frequency based onthe number of objects that enter the waiting line within the set timeperiod. The passage frequency calculation unit 104 can correct thecalculated first passage frequency and second passage frequency by usingEquations 2 and 3 described below in the description of step S205.

In step S205, the waiting time estimation unit 106 performs the waitingtime estimation at a time of the waiting time estimation indicated bythe setting information determined in step S201 in a following manner.That is, the waiting time estimation unit 106 acquires an estimatedvalue of waiting time in the waiting line based on the number of objectsacquired in step S203 and the first passage frequency acquired in stepS204. The waiting time estimation unit 106 then records the acquiredwaiting time in the memory 110 or the like. The waiting time estimationunit 106 acquires a value estimated as waiting time in the waiting line,for example, by using following Equation 1:

WTp=QL/(γTH′exit+(1−γ)TH′entry)  (Equation 1)

-   -   WTp: Estimated Waiting Time    -   QL: Number of Objects    -   TH′exit: Corrected Passage Frequency (Exit (Getting-in Gate))    -   TH′entry: Corrected Passage Frequency (Entrance (Entering Gate))    -   Γ: Exit Reflecting Coefficient (0≦γ≦1)

In the present exemplary embodiment, γ=1. TH′exit in Equation 1indicates the corrected first passage frequency. TH′entry indicates thecorrected second passage frequency. In step S204, the passage frequencycalculation unit 104 calculates the corrected passage frequencies inEquation 1 using following Equations 2 and 3:

$\begin{matrix}{{{TH}^{\prime}{exit}} = {{{Kp} \cdot {THexit}} + {{Kd} \cdot \frac{d\; {THexit}}{dt}} + {{Ki} \cdot {\int{{THexit}\; {dt}}}}}} & \left( {{Equation}\mspace{14mu} 2} \right)\end{matrix}$

-   -   THexit: Actually Calculated Passage Frequency (Exit (Getting-in        Gate))    -   Kp, Kd, and Ki: Coefficient

$\begin{matrix}{{{TH}^{\prime}{entry}} = {{{Kp} \cdot {THentry}} + {{Kd} \cdot \frac{d\; {THentry}}{dt}} + {{Ki} \cdot {\int{{THentry}\; {dt}}}}}} & \left( {{Equation}\mspace{14mu} 3} \right)\end{matrix}$

-   -   THentry: Actually Calculated Frequency (Entrance (Entering Gate)    -   Kp, Kd, and Ki: Coefficient

In the present exemplary embodiment, the passage frequency calculationunit 104 calculates the corrected passage frequencies using Equations 2and 3 where Kp=1, Kd=0, and Ki=0. In other words, in the presentexemplary embodiment, the corrected passage frequency has the same valueas the original passage frequency. The passage frequency calculationunit 104 can use values of the coefficients Kp, Kd, and Ki, which areadjusted such that the waiting time calculated using Equations 1 to 3for an actual waiting line matches the actually observed waiting time.In addition to the method using Equations 1 to 3, the waiting timeestimation unit 106 can calculate an estimated value of waiting time inthe waiting line using a method of making a correction based ondifferential value representing tendency of change amount and tendencyof past data.

The setting unit 105 can previously determine the initial value ofpassage frequency as setting information in consideration of a casewhere the passage frequency becomes 0, for example, when the waitingtime estimation system is activated. In addition, when the passagefrequency is 0, the display unit 108 can display preset information,e.g., a character string such as “Measuring Waiting Time”, on thedisplay apparatus 130.

In step S206, the display unit 108 displays information indicating theestimated value of the waiting time acquired in step S205 on the displayapparatus 130. The display unit 108 can display on the display apparatus130 information such as a past estimated value of waiting time, thefirst passage frequency, and the second passage frequency.

In step S207, the communication unit 107 determines whether to transmitthe information about the waiting time acquired in step S205 to anexternal terminal device based on, for example, the setting informationstored in the memory 110 and a request from an external terminal device.If the communication unit 107 has determined that the information aboutthe waiting time acquired in step S205 is to be transmitted to theexternal terminal device, the communication unit 107 transmits theinformation about the waiting time acquired in step S205 to the externalterminal device.

In step S208, the waiting time estimation unit 106 determines, based on,for example, an operation by a user through the input apparatus 120,whether an instruction to terminate the acquiring processing of waitingtime in the waiting line has been accepted. The waiting time estimationunit 106 terminates the processing of FIG. 2 if the waiting timeestimation unit 106 determines that an instruction to terminate theacquiring processing of waiting time in the waiting line has beenaccepted (Yes in step S208). If the waiting time estimation unit 106determines that an instruction to terminate the acquiring processing ofwaiting time in the waiting line has not been accepted (No in stepS208), the processing proceeds to step S202.

In the description of FIG. 2, steps S203, S204, and steps S206 and S207are described as sequential processing. The count unit 103, the passagefrequency calculation unit 104, and the waiting time estimation unit 106can, for example, write the calculation results in steps S203, S204, andS205 in a database or a file stored in the memory 110. The waiting timeestimation unit 106, the display unit 108, and the communication unit107 can then perform processing for reading the contents of a databasesor a file stored in the memory 110 as processing independent from theprocessing of steps S203 to S205 in parallel with the processing ofsteps S203 to S205.

The waiting time estimation system and the external terminal device canbe connected through a network and the external terminal device canrequest the communication unit 107 to transmit the waiting time data andthe like. In response to the request, the external terminal device candisplay data transmitted from the communication unit 107 on a displayapparatus of the terminal device.

Next, an operation example of the waiting time estimation system whenthe processing of the flowchart of FIG. 2 is performed will bedescribed. In the example of FIGS. 3A and 3B, the first passagedetection unit 101 and the second passage detection unit 102 includeinfrared sensors.

FIGS. 3A and 3B illustrate an exemplary application of the waiting timeestimation system. An example in which the processing of the waitingtime estimation system is applied to a line at a taxi stand will bedescribed with reference to FIGS. 3A and 3B.

FIG. 3A illustrates a taxi stand depicting a taxi 301 arriving within anarea 3001. Area 3002 is an area where people waiting for a taxi line up.

Within the area 3002, there is an exit 302 that is a place for a personto get in a taxi and an entrance 303 that is a place to enter the area3002. Guide signs 304 specifies the area 3002 and prompts the peoplewaiting for a taxi to form a line. Instead of the guide signs 304, aline or the like for indicating a place to enter the area 3002 and aroute of the line can be drawn on the floor.

An infrared sensor 305, which is the first passage detection unit 101,is installed above the exit 302. An infrared sensor 306, which is asecond passage detection unit 102, is installed above the entrance 303.A display monitor 307 corresponding to the display apparatus 130 forpresenting estimated waiting time is installed near the entrance 303.

The example in FIG. 3A illustrates a state where a waiting line is notyet formed and there is no person in the area 3002.

Since no waiting line for taxis is formed as illustrated in FIG. 3A, thenumber of waiting people is zero in the count in step S203 in theprocessing flow described in the flowchart of FIG. 2. Thus, regardlessof passage frequency, waiting time estimated in step S205 is zerominutes (none). This is because QL of Equation 1 becomes 0, so that anestimated value of waiting time in the waiting line calculated usingEquation 1 becomes zero.

Next, FIG. 3B illustrates a state that has changed from the stateillustrated in FIG. 3A. In the new state, a waiting line is formed, andsome people have gotten into a taxi. FIG. 4 is an example of result ofwaiting time estimation processing in the state of FIG. 3B. The table ofFIG. 4 is an exemplary table displayed on the display monitor 307 by thewaiting time estimation system.

Downward pointing triangular symbols in the table of FIG. 4 are symbolsrepresenting times at which events occur. In the example of FIG. 4, thewaiting time estimation system performs the processing of FIG. 2 every30 seconds. In the example of FIG. 4, the waiting time estimation unit106 calculates the corrected passage frequency that is the first passagefrequency after correction. In this case, the corrected passagefrequency is a value obtained by dividing the number of detectedpassages through the exit within two minutes before the calculation, bytwo minutes. That is, the waiting time estimation unit 106 calculatesTH′exit using Equation 2 where Kp=2, Kd=0, and Ki=0. For example, instep S201, the setting unit 105 determines how much the values of thecoefficients Kp, Kd, and Ki are to be set, and stores the determinedinformation as setting information in the memory 110 or the like.

Since the estimated waiting time is calculated by using Equation 1, itis necessary to prevent a denominator on the right side of Equation 1from becoming zero. Therefore, when there is no human body in thewaiting line that passes through the entrance and the exit of thewaiting line within a set time period, in order to prevent the firstpassage frequency and the second passage frequency from becoming zero,the passage frequency calculation unit 104 calculates corrected passagefrequency using elapsed time from the latest detection of passage of ahuman body as a unit time. For example, when one person has passedthrough the exit within a set time period including time 5 minutesbefore and no person has passed after that, the passage frequencycalculation unit 104 calculates the corrected passage frequency of thefirst passage frequency and ⅕=0.2 is obtained.

In the example of FIG. 4, waiting time calculated by the waiting timeestimation unit 106 using Equation 1 is displayed in minutes. However,when the waiting time is less than or equal to a set threshold, e.g.,for example, 3 minutes, the display unit 108 can display a characterstring such as “Waiting Time is 3 Minutes or Less” on the displaymonitor 307.

As described above, in the present exemplary embodiment, the waitingtime estimation system calculates an estimated value of waiting time inthe waiting line based on the number of people in the waiting line andfrequency of the people exiting the waiting line. As a result, thewaiting time estimation system can more accurately estimate the waitingtime in the waiting line even when service time is not constant.

In addition, since the first passage detection unit 101 and the secondpassage detection unit 102 detect passage of people at the exit and theentrance in the waiting line, information about the people whoenter/exit the waiting line does not need to be acquired individually atthe timing of the entrance/exit.

In the above-described example of the present exemplary embodiment, thewaiting time estimation system acquires an estimated value of waitingtime in the waiting line of taxis. However, the waiting time estimationsystem can acquire the estimated value of waiting time in, for example,a waiting line formed to enter a restaurant, a waiting line at a cashregister in a store, a waiting line at an airport counter, or a waitingline at an airport security check.

A second exemplary embodiment will be described below. In the firstexemplary embodiment, the waiting time estimation system detects humanbodies in the waiting line that pass through the entrance and the exitusing the first passage detection unit 101 and the second passagedetection unit 102, which are infrared sensors.

In the second exemplary embodiment, the waiting time estimation systemdetects human bodies in the waiting line passing through the entranceand the exit based on images of the waiting line captured by an imagingapparatus 501.

FIG. 5 illustrates an exemplary system configuration of the waiting timeestimation system according to the present exemplary embodiment.

The waiting time estimation system according to the present exemplaryembodiment includes an information processing apparatus 100 and animaging apparatus 501. The information processing apparatus 100 and theimaging apparatus 501 are communicably connected through a network 520.The network 520 can include, for example, a plurality of routers,switches, and cables that satisfy communication standards such asEthernet. In the present exemplary embodiment, any communicationstandards, scales, and configurations are acceptable as long as theyallow communication between the imaging apparatus 501 and theinformation processing apparatus 100. For example, the network 52 caninclude the Internet, a wired local area network (LAN), a wireless LAN,and a wide area network (WAN).

The imaging apparatus 501 is an imaging apparatus such as a networkcamera. In the present exemplary embodiment, the information processingapparatus 100 drives the imaging apparatus 501, acquires captured imagesfrom the imaging apparatus 501, and perform other operations. Anexemplary hardware configuration of each system component of the waitingtime estimation system will be described with reference to FIG. 5.

The hardware configuration of the information processing apparatus 100of the present exemplary embodiment is similar to the first exemplaryembodiment. The CPU 111 performs processing based on a program stored inthe memory 110 or the like, thereby realizing functions of theinformation processing apparatus 100 described below with reference toFIG. 6 and the processing of the flowchart of FIG. 2.

The imaging apparatus 501 includes a memory 510, a CPU 511, an imagingunit 512, a signal processing unit 513, a drive control unit 514, and acommunication control unit 515.

The memory 510 is a storage device that stores various programs, varioustypes of setting data, image data obtained by photographing a waitingline, and the like. The CPU 511 is a central processing unit thatcontrols the processing of the imaging apparatus 501.

The imaging unit 512 includes an image sensor and an optical system, andcaptures an image with an intersection of the optical axis of theoptical system and the image sensor as an imaging center. The imagesensor is sensor such as a complementary metal-oxide semiconductor(CMOS) sensor or a charged coupled device (CCD) sensor.

The signal processing unit 513 performs signal processing on an imagesignal obtained by capturing an image by the imaging unit 512. Forexample, the signal processing unit 513 codes an image signal of animage captured by the imaging unit 512 The signal processing unit 513can use a variety of coding schemes such as Joint Photographic ExpertsGroup (JPEG), H.264/MPEG-4 AVC (hereinafter referred to as H.264), orHigh Efficiency Video Coding (HEVC).

The drive control unit 514 controls the imaging unit 512 to change animaging direction and an imaging angle of view. In the present exemplaryembodiment, the imaging unit 512 can change the imaging direction to apanning direction or a tilt direction. The imaging apparatus 501 doesnot need to be able to change the imaging direction or change the angleof view.

The communication control unit 515 is a unit used for communication withan external device, such as the information processing apparatus 100,through the network 520. The communication control unit 515 transmitsinformation of the captured image on which processing has been performedby the signal processing unit 513 to the information processingapparatus 100. The communication control unit 515 receives a controlcommand for the imaging apparatus 501 transmitted from the informationprocessing apparatus 100.

The CPU 511 performs processing based on a program stored in the memory510 or the like, thereby realizing functions of the imaging apparatus501 and processing of the imaging apparatus 501.

FIG. 6 illustrates an exemplary functional configuration of theinformation processing apparatus 100 according to the present exemplaryembodiment. The information processing apparatus 100 according to thepresent exemplary embodiment includes a passage detection unit 502, acount unit 103, a passage frequency calculation unit 104, a setting unit105, a waiting time estimation unit 106, a communication unit 107, and adisplay unit 108. The information processing apparatus 100 of thepresent exemplary embodiment is different from the first exemplaryembodiment in that it includes the passage detection unit 502. Thesetting unit 105, the waiting time estimation unit 106, thecommunication unit 107, and the display unit 108 are similar to those inthe first exemplary embodiment, and descriptions thereof will not berepeated.

The passage detection unit 502 detects passage through the entrance andthe exit in a waiting line of objects. In the present exemplaryembodiment, the passage detection unit 502 acquires an image of thewaiting line from the imaging apparatus 501. The passage detection unit502 detects passage of an object based on the image acquired from theimaging apparatus 501. The imaging apparatus 501 is installed such thatthe imaging apparatus 501 can photograph the entire waiting line.

The passage detection unit 502 acquires an image captured by the imagingapparatus 501 as a moving image (a plurality of sequential images at aset interval). The passage detection unit 502 processes and analyzeseach image included in the acquired moving image to detect an object.The passage detection unit 502 then detects passage of the object at setpositions, e.g., the entrance and the exit of the waiting line, based ontemporal change of the position of the object. The passage detectionunit 502 can determine a plurality of positions for detecting passage ofan object in images. The passage detection unit 502 can detect passageof an object through each determined position.

The count unit 103 detects objects from an image obtained by the imagingapparatus 501 through image processing and image analysis, and countsthe number of detected objects. In a case where the imaging apparatus501 photographs an object existing in an area other than the line, thecount unit 103 can be configured to detect objects coming just from thepreset area within an image to count the objects.

The passage frequency calculation unit 104 calculates frequency of anobject passing through the set position within the preset time periodbased on passage of the object through the set positions detected by thepassage detection unit 502. The passage frequency calculation unit 104calculates the passage frequency based on the state of the waiting lineand a renewal interval in displaying estimated waiting time.

An exemplary processing of the information processing apparatus 100according to the second exemplary embodiment will be described withreference to FIG. 2. The processing in the flowchart of FIG. 2 starts,for example, when the waiting time estimation system is activated. Theprocessing in step S201 is similar to that in the first exemplaryembodiment.

In step S202, the passage detection unit 502 detects passage of anobject through the set position (the entrance or the exit of the waitingline) based on an image of the waiting line captured by the imagingapparatus 501. In step S203, the count unit 103 analyzes the imagecaptured by the imaging apparatus 501 and counts objects in the waitingline. In step S204, the passage frequency calculation unit 104calculates passage frequency through the set position of objects withinthe set time period based on detection of passage of an object by thepassage detection unit 502.

Also in the present exemplary embodiment, similar to the first exemplaryembodiment, the passage frequency calculation unit 104 acquiresfrequency of an object that has exited the waiting line within the settime period as first passage frequency. In addition, the passagefrequency calculation unit 104 acquires frequency of an object that hasentered the waiting line within the set time period as second passagefrequency. The passage frequency calculation unit 104 can store theacquired first passage frequency in the memory 110 or the like.

The processing of steps S205 to S208 is similar to that of the firstexemplary embodiment. In step S204, the passage frequency calculationunit 104 calculates the corrected first passage frequency and thecorrected second passage frequency using Equations 2 and 3 similar tothe first exemplary embodiment, but coefficients of Equations 2 and 3are different from those in the first exemplary embodiment.

In the present exemplary embodiment, the passage frequency calculationunit 104 calculates the corrected first passage frequency and thecorrected second passage frequency using Equations 2 and 3 where γ=1,Kp=1, Kd=0.1, Ki=0 in step S204. In the present exemplary embodiment,the coefficient Kd in Equations 2 and 3 is 0.1, and thus the timedifferential values of the first passage frequency and the secondpassage frequency are reflected. Therefore, the passage frequencycalculation unit 104 can calculate the corrected first passage frequencyand the corrected second passage frequency in which historical tendencyof passage of an object is reflected.

As a result, the waiting time estimation unit 106 can calculate anestimated value of the waiting time in which historical tendency ofpassage of an object is reflected. As a result, the waiting timeestimation unit 106 can acquire a more accurate estimated value ofwaiting time in which the historical tendency of passage of an object isalso taken into consideration.

Since γ=1 in the present exemplary embodiment, the waiting timeestimation unit 106 calculates an estimated value of waiting time takingonly the frequency of an object exiting the waiting line intoconsideration. However, by setting the value of γ to a value other than1, the waiting time estimation unit 106 can calculate an estimated valueof waiting time taking not only the frequency of an object exiting thewaiting line but also the frequency of an object entering the waitingline into consideration.

In the description of FIG. 2, steps S203, S204, and steps S206 and S207are described as sequential processing. The count unit 103, the passagefrequency calculation unit 104, and the waiting time estimation unit 106can write the calculation results in steps S203, S204, and S205 in adatabase or a file stored in the memory 110. The waiting time estimationunit 106, the display unit 108, and the communication unit 107 can thenread the contents of a database or a file stored in the memory 110 asprocessing independent from the processing of steps S203 to S205, and inparallel to the processing of steps S203 to S205.

The waiting time estimation system and the external terminal device canbe connected through a network. The external terminal device can requestthe communication unit 107 to transmit the waiting time data and thelike, and in response to the request, the external terminal device candisplay data transmitted from the communication unit 107 on a displayapparatus of the terminal device.

FIGS. 7A to 7F illustrate exemplary application of the waiting timeestimation system.

FIG. 7A illustrates an exemplary image of a waiting line for taxiscaptured by the imaging apparatus 501. The passage detection unit 502and the count unit 103 detect upper bodies of human bodies from theimage of FIG. 7A, thereby detecting human bodies. A detected human bodyframe 701 is a frame indicating the upper bodies of the detected humanbodies. The display unit 108 can generate the detected human body frame701 based on a detected center position and a size of the upper bodiesof the human bodies, and display the detected human body frame 701 overthe image captured by the imaging apparatus 501 on the display apparatus130 or the like.

A passage detection segment 702 is a segment indicating a portionthrough which an object passes to be detected. The setting unit 105 candetermine the passage detection segment 702 as follows as an example.The setting unit 105 instructs the display unit 108 to display, on thedisplay apparatus 100, a passage detection segment specifying screenthat is used to specify the passage detection segment 702. The passagedetection segment specifying screen includes the image captured by theimaging apparatus 501.

The setting unit 105 then accepts specification of the passage detectionsegment 702 performed by a user who operates on the passage detectionsegment specifying screen through the input apparatus 120. For example,the user draws a segment by dragging a mouse at a position where theuser desires to specify the passage detection segment on an imagecaptured by the imaging apparatus 501 included in the passage detectionsegment specification screen, thereby specifying passage detectionsegment 702. The setting unit 105 can accept such specification from theuser and determine the segment indicated by the accepted specificationas the passage detection segment 702.

When a person detected as a detected human body frame 701A movesforward, as illustrated in FIG. 7B, to get in a taxi, in step S202, thepassage detection unit 502 tracks the person corresponding to thedetected human body frame 701A. The passage detection unit 502recognizes that the person corresponding to the detected human bodyframe 701A in FIG. 7B has passed through the passage detection segment702 from the state of FIG. 7A. As described above, the passage detectionunit 502 recognizes whether a certain person has passed through thepassage detection segment 702 based on change in position of the sameperson in consecutive image frames in the moving image acquired from theimaging apparatus 501.

FIG. 8 is an example result of waiting time estimation processing in thestate illustrated in FIG. 7. The table in FIG. 8 is an example tabledisplayed on the display apparatus 130 by the waiting time estimationsystem. Downward pointing triangular symbols in the table of FIG. 8represent the timing at which events occur. In the example of FIG. 8,the waiting time estimation system performs the processing of FIG. 2every 30 seconds.

In step S203, the count unit 103 counts the number of human bodies,which are objects, existing in the image of FIG. 7B. When the count unit103 counts the number of objects from the image captured by the imagingapparatus 501 in step S203, the count unit 103 can detect objects from aset area in the image and count the number of the detected objects. Anarea 703 in FIG. 7C is an example area for counting objects that is setto distinguish people in the waiting line from passersby.

The setting unit 105 can determine the area for counting objects asfollows. The setting unit 105 instructs the display unit 108 to display,on the display apparatus 130, an area specification screen used forspecifying an area for counting objects. The area specification screenincludes an image captured by the imaging apparatus 501. The settingunit 105 accepts specification of an area for counting objects specifiedby a user, according to an operation on the area specification screen bythe user through the input apparatus 120.

For example, the user specifies an area by clicking points of an areausing a mouse where the user desires to specify as corners on an imagecaptured by the imaging apparatus 501 included in the area specificationscreen. The setting unit 105 can accept such specification from the userand determine the area indicated by the points of the acceptedspecification as the area 703.

The setting unit 105 can determine the passage detection segment fordetecting people entering the waiting line in the image captured by theimaging apparatus 501. A passage detection segment 704 in FIG. 7D is anexample segment used for detecting an object entering the waiting line.The setting unit 105 can determine the passage detection segment 704 inthe same manner as the passage detection segment 702.

In addition, as illustrated in FIG. 7E, the setting unit 105 candetermine the passage detection segment for detecting an object exitingthe waiting line and the area for counting objects, within the imagingapparatus 501. The waiting time estimation system then counts the numberof objects in the waiting line by using one of or both the passagedetection segment for detecting an object exiting the waiting line andthe area for counting objects.

The count unit 103 can use both of the passage detection segments withinone image to count the number of objects in the waiting line. One of thepassage detection segments is used to detect an object exiting thewaiting line and the other of the passage detection segments is used todetect an object entering the waiting line.

In the present exemplary embodiment, the waiting line is a line ofpeople waiting for taxis. Since it is assumed that a child typicallydoes not enter a taxi alone, but does so with an adult, the waiting timeestimation system can regard just adults as people in the waiting line.

It can be assumed that children are shorter than adults. Therefore, inthis case, the setting unit 105 determines a position of the area 703for counting objects and a position of the passage detection segment 702to be higher than those in the case of FIG. 7C, as illustrated in FIG.7F, such that the whole upper bodies of children are not included. As aresult, the count unit 103 and the passage detection unit 502 can detectupper bodies of adult human bodies without detecting upper bodies ofchild human bodies. In addition, the count unit 103 and the passagedetection unit 502 detect human bodies by detecting upper bodies ofhuman bodies. Thus, human bodies can be more accurately detectedcomparing to detection of the whole human bodies.

When the waiting line is a line of people waiting for an amusementfacility for children, it is assumed that adults do not use theamusement facility. Therefore, the waiting time estimation system canregard the objects in the waiting line as children. It can be assumedthat adults are taller than children. Therefore, in this case, thesetting unit 105 determines that a position of the area 703 for countingobjects and a position of the passage detection segment 702 are to belower than those in the case of FIG. 7C, so that the whole upper bodiesof the adult are not included. As a result, the count unit 103 and thepassage detection unit 502 can detect upper bodies of child human bodieswithout detecting upper bodies of adult human.

In the present exemplary embodiment, the imaging apparatus 501 isinstalled to photograph the waiting line from an oblique direction. Suchan installation enables the imaging apparatus 501 to photograph humanbodies in the waiting line without overlapping with each other. Thus,the waiting time estimation system can more accurately detect humanbodies from an image.

The passage detection unit 502 detects passage of an object through thepassage detection segments 702 and 704 by detecting the same object inboth ends of the area spanning the passage detection segments 702 and704 within the image. For example, if the passage detection segment 702exists near the right end of the image, an area on the right side of thepassage detection segment 702 becomes so narrow that the entire objectcannot be photographed, and the passage detection unit 502 cannot detectthe object.

Therefore, the setting unit 105 can determine that positions of thepassage detection segments 702 and 704 are set such that both ends ofthe area spanning the passage detection segments 702 and 704 within theimage have a size enabling detection of an object. For example, thesetting unit 105 can determine positions of the passage detectionsegments 702 and 704 such that both ends of the area spanning thepassage detection segments 702 and 704 within the image have a size thatis larger than the size of an object to be detected. Accordingly, thepassage detection unit 502 can more stably detect an object passingthrough the passage detection segments 702 and 704 and accuracy ofwaiting time estimation can be improved.

As described above, according to the present exemplary embodiment, thewaiting time estimation system counts the number of people in thewaiting line and detects people exiting the waiting line based on animage of the waiting line acquired by the imaging apparatus 501. In thismanner, the waiting time estimation system can perform waiting timeestimation processing based on an image of the waiting line. Thus,devices such as infrared sensors for detecting passage of people do notneed to be individually installed at set positions of a waiting line.Therefore, a configuration of the waiting time estimation system can besimplified.

A third exemplary embodiment will be described below. In the secondexemplary embodiment, it is assumed that the single imaging apparatus501 photographs the entire waiting line. In the present exemplaryembodiment, an area in which a waiting line exists is larger than thesecond exemplary embodiment, and a plurality of imaging apparatusesphotographs each portion of the waiting line. In addition, in the firstand second exemplary embodiments, there is one exit of the waiting line.In the present exemplary embodiment, there is a plurality of exits ofthe waiting line.

The system configuration of the waiting time estimation system accordingto the present exemplary embodiment, the hardware configuration, and thefunctional configuration of the respective system components are similarto those of the second exemplary embodiment. In the present exemplaryembodiment, the imaging apparatus 501 includes a plurality of imagingapparatuses.

FIG. 9 illustrates exemplary application of the waiting time estimationsystem in the present exemplary embodiment. An exemplary waiting line ata taxis stand on which the waiting time estimation processing isperformed will be described with reference to FIG. 9. Differences fromFIG. 3 will be described.

Areas 9001 and 9002 are areas where taxis arrive. Taxis do not arrive atone, but rather two areas. Taxis 901 and 902 respectively arrive withinranges of the areas 9001 and 9002.

An area 9003 is an area where people waiting for a taxi line up. Thearea 9003 is larger than the area 3002 and includes two getting-inpositions 903 and 904 for passengers of taxis. The getting-in positions903 and 904 are also exits in the waiting line. For example, anattendant guides people 912 waiting for a taxi near the getting-inposition 904 to the getting-in position 903 or the getting-in position904 where they should wait.

In order to photograph the waiting line at the taxi stand as illustratedin FIG. 9, a plurality of cameras 907 to 909 is installed. Similar tothe second exemplary embodiment, images captured by the cameras 907 and908 are used for detecting passage of an object through the getting-inpositions (exits of the waiting line). The cameras 907 to 909 are theimaging apparatus 501 in the present exemplary embodiment.

In order that a count unit 103 can completely count the number of peoplein the waiting line at the taxi stand based on the images captured bythe cameras 907 to 909, the respective cameras 907 to 909 are arrangedsuch that photographing areas thereof overlap with each other. Thephotographing area 907A in FIG. 9 is an area indicating a photographingrange of the camera 907. The photographing area 908A in FIG. 9 is anarea indicating a photographing range of the camera 908. Thephotographing area 909A in FIG. 9 is an area indicating a photographingrange of the camera 909.

FIG. 10A illustrates an exemplary image captured by the camera 907. FIG.10B illustrates an exemplary image captured by the camera 908. In thiscase, the area 1001 and the area 1002 overlap with each other. Thus, thesetting unit 105 determines detection target areas 1003 and 1004 suchthat an object is not detected in duplication. For example, the settingunit 105 determines the areas 1003 and 1004 in a manner similar to themanner in which the area 703 in FIG. 7C is determined in the secondexemplary embodiment.

FIG. 11 illustrates an exemplary system configuration of the timeestimation system according to the present exemplary embodiment. A blockdiagram is illustrated in FIG. 11

The cameras 907 to 909 photograph the waiting line in a taxi waitingarea 1101. A passage detection unit 502 in an information processingapparatus 100 detects an object that has passed through a set passagedetection segment based on images captured by the cameras 907 to 909,and notifies the time at which the object has passed through the passagedetection segment to a waiting time estimation unit 106.

The setting unit 105 determines a segment, which is specified throughthe passage detection setting graphical user interface (GUI) 1106, asthe passage detection segment. The passage detection setting GUI 1106 isused for specifying the passage detection segment. The passage detectionsegment specification screen described in the second exemplaryembodiment is an example of the passage detection setting

GUI 1106. In the present exemplary embodiment, the informationprocessing apparatus 100 is a single information processing apparatus.However, when the number of images captured by the cameras 907 to 909increases and it is difficult for a single information processingapparatus to process all of these images within a set time period, aplurality of information processing apparatuses can distributivelyprocess the respective images.

In this case, the information processing apparatus 100 includes aplurality of information processing apparatuses. The cameras 907 to 909can include a function of counting the number of objects within a setarea, and a function of detecting an object that has passed through theset passage detection segment. In this case, the cameras 907 to 909transmit to the information processing apparatus 100 information such asthe number of objects within the set area and the detection result of anobject that has passed through the set passage detection segment, inaddition to the captured image.

The setting unit 105 determines an area specified through a people countsetting GUI 1107 as the area for counting objects. The people countsetting GUI 1107 is used for specifying the area for counting objects.The area specification screen described in the second exemplaryembodiment is an example of the people count setting GUI 1107.

The count unit 103 counts the number of objects included in the areadetermined through the people count setting GUI 1107 within imagescaptured by the cameras 907 to 909 at set timing. The waiting timeestimation system uses one or more of the images captured by the cameras907 to 909 based on the waiting state of the waiting line for countprocessing of objects in the waiting line.

The count unit 103 does not necessarily perform count processing ofobjects in the waiting line based on a moving image from the imagingapparatus 501, but can perform the count processing based on a stillimage acquired from the imaging apparatus 501 at set timing.

The load put on resources such as the CPU 111 can be reduced in thecount processing of objects within the waiting line when the count unit103 acquires one still image at a set time compared to the countprocessing when the count unit 103 acquires a moving image at all times.In addition, this configuration is exemplary because the number ofcameras increases that one information processing apparatus can use incount processing of people.

As illustrated in FIG. 12, the waiting time estimation system canacquire images captured at the same time from the cameras, andsequentially start analysis processing on the acquired images, such ascount processing of objects in the waiting line and passage detectionprocessing of an object through the passage detection segments. Thus,processing can be performed on images captured at the same time by theplurality of cameras. Therefore, it is possible to avoid redundantlycounting the same person who has been moving in the waiting line andphotographed by different cameras. This also reduces the processing loadon the CPU 111.

When counting the number of objects in the waiting line based on stillimages captured at regular intervals, the count unit 103 acquires onlythe number of objects within the waiting line at the time that the stillimage is captured. In this case, the count unit 103 can count the numberof objects within the waiting line at a time other than the time ofcapturing still images.

More specifically, the count unit 103 acquires the number of objects inthe waiting line at a set time based on images captured at the time.After the acquisition, the count unit 103 increments the number ofacquired objects by one every time when the passage detection unit 502detects an object passing through the entrance of the waiting line untilnext acquisition of still images from the cameras.

In addition, the count unit 103 decrements the number of acquiredobjects by one each time the passage detection unit 502 detects anobject passing through the exit of the waiting line after theacquisition until the next acquisition of still image. Accordingly, thecount unit 103 can reduce the load on the CPU 111 by correcting thenumber of objects in the waiting line each time passage of an objectthrough the entrance or the exit of the waiting line is detected, and inaddition, can correctly count the number of people in the waiting line.

The passage frequency calculation unit 104 calculates the first passagefrequency, which is frequency of an object that exits the waiting line,based on time when the object has passed through the passage detectionsegment. The time is transmitted from the passage detection unit 502.The waiting time estimation unit 106 then calculates an estimated valueof waiting time based on the calculated first passage frequency and thenumber of objects in the waiting line counted by the count unit 103.When the waiting line is photographed by a plurality of cameras, thecount unit 103 counts the number of objects in the waiting line bysumming up the numbers of objects in the set areas for counting objectsin the respective images obtained by the plurality of cameras.

The waiting time estimation unit 106 stores the calculated informationabout the waiting time in the database 1109, which can be a commaseparated values (CSV) file or the like stored in the memory 110. Thecommunication unit 107 can transmit the information about the waitingtime calculated by the waiting time estimation unit 106 to anotherexternal terminal device. In addition, the display unit 108 can displaythe information on an external monitor 1110 or the like. The monitor1110 is a display apparatus such as a digital signage device, and is oneexample of the display apparatus 130. The waiting time estimation unit106 can store not only the information about the calculated waitingtime, but also the information such as time when an object has passedthrough the passage detection segment, the number of objects in thewaiting line, and the like in a database stored in the memory 110. Thedisplay unit 108 can display the information stored in the databasestored in the memory 110 such as time when an object passes through thepassage detection segment, the number of objects in the waiting line,and the like, on the monitor 1110 or the like.

The waiting time estimation system can periodically calculate anestimated value of waiting time and display the calculated estimatedvalue of waiting time on the display apparatus 130 at preset intervals.Alternatively, the waiting time estimation system can calculate anestimated value of waiting time and display the calculated estimatedvalue of waiting time on the display apparatus 130 each time the passagedetection unit 502 detects an object that has passed through theentrance and the exit of the waiting line. That is, each time thepassage detection unit 502 detects an object that has passed through theentrance and the exit of the waiting line, the count unit 103 counts thenumber of people in the waiting line. In addition, each time the passagedetection unit 502 detects an object that has passed through theentrance or the exit of the waiting line, the passage frequencycalculation unit 104 calculates the first passage frequency, the secondpassage frequency, the corrected first frequency, and the correctedsecond passage frequency. The waiting time estimation unit 106 thenacquires an estimated value of waiting time based on the number countedby the count unit 103 and the passage frequencies calculated by thepassage frequency calculation unit 104.

Thus, the waiting time estimation system can present the latestestimated waiting time to people who are about to get in the waitingline. If display frequency on the display apparatus 130 is raised beyondan appropriate rate, visibility of display decreases. Therefore, thedisplay unit 108 can perform processing as follows when passage of anobject is detected at the entrance or the exit of the waiting line. Thatis, the display unit 108 can renew the display on the display apparatus130 only if the time period from renewal of the display on the displayapparatus 130 when a person previously enters or exits the waiting line,until a person enters or exits this time, is longer than a threshold.When no object passing through the entrance or the exit of the waitingline is detected, it is desirable that the waiting time estimationsystem calculate an estimated value of waiting time and renew thedisplay on the display apparatus 130 when a set time period has elapsedfrom the latest renewal time of the display on the display apparatus130.

In the present exemplary embodiment, the setting unit 105 determinesonly one area for counting the number of people within an image capturedby one camera, but as illustrated in FIG. 13A, the setting unit 105 candetermine two or more areas.

The setting unit 105 determines one passage detection segment in oneimage. However, as illustrated in FIG. 13B, when one camera is arrangedsuch that the camera can photograph a plurality of getting-in positions,the setting unit 105 can determine a plurality of passage detectionsegments within an image captured by the camera. In this case, thepassage detection unit 502 detects passage of an object through eachpassage detection segment. Based on the total of objects that passedthrough the respective detected passage detection segments, the passagefrequency calculation unit 104 calculates the first passage frequency orthe second passage frequency.

When the count unit 103 counts the number of objects in an area 913 inFIG. 9, the display unit 108 can display the following information onthe display monitor 911 when the counted number of objects in the area913 becomes less than or equal to a set threshold. That is, the displayunit 108 can display information on the display monitor 911 to promptthe people 912 who are waiting in the waiting line and have not enteredthe area 913 to move to the getting-in position in front.

As described above, according to the processing of the present exemplaryembodiment, the waiting time estimation system can acquire an estimatedvalue of waiting time with improved accuracy even when portions of awaiting line are divided and photographed by a plurality of cameras orwhen a plurality of exits exists in the waiting line.

OTHER EMBODIMENTS

The first to third exemplary embodiments are not seen to be limiting.Various modifications and changes are possible within the scope each ofthese embodiments.

One or more functions of the above exemplary embodiments can be realizedby a program that is provided to a system or an apparatus through anetwork or a storage medium and read and executed by one or moreprocessors in a computer of the system or the apparatus. The one or morefunctions can also be realized by a circuit (e.g., application specificintegrated circuit (ASIC)).

Although exemplary embodiments have been described in detail above, thepresent disclosure is not limited to such specific exemplaryembodiments. For example, part of or entire functional configuration ofthe above-described waiting time estimation system can be implemented ashardware in the information processing apparatus 100.

OTHER EMBODIMENTS

Embodiment(s) can also be realized by a computer of a system orapparatus that reads out and executes computer executable instructions(e.g., one or more programs) recorded on a storage medium (which mayalso be referred to more fully as a ‘non-transitory computer-readablestorage medium’) to perform the functions of one or more of theabove-described embodiment(s) and/or that includes one or more circuits(e.g., application specific integrated circuit (ASIC)) for performingthe functions of one or more of the above-described embodiment(s), andby a method performed by the computer of the system or apparatus by, forexample, reading out and executing the computer executable instructionsfrom the storage medium to perform the functions of one or more of theabove-described embodiment(s) and/or controlling the one or morecircuits to perform the functions of one or more of the above-describedembodiment(s). The computer may comprise one or more processors (e.g.,central processing unit (CPU), micro processing unit (MPU)) and mayinclude a network of separate computers or separate processors to readout and execute the computer executable instructions. The computerexecutable instructions may be provided to the computer, for example,from a network or the storage medium. The storage medium may include,for example, one or more of a hard disk, a random-access memory (RAM), aread only memory (ROM), a storage of distributed computing systems, anoptical disk (such as a compact disc (CD), digital versatile disc (DVD),or Blu-ray Disc (BD)™), a flash memory device, a memory card, and thelike.

While exemplary embodiments have been described, it is to be understoodthat the invention is not limited to the disclosed exemplaryembodiments. The scope of the following claims is to be accorded thebroadest interpretation so as to encompass all such modifications andequivalent structures and functions.

This application claims the benefit of Japanese Patent Application No.2016-168215, filed Aug. 30, 2016, which is hereby incorporated byreference herein in its entirety.

What is claimed is:
 1. An information processing apparatus comprising: afirst acquisition unit configured to acquire a number of objects in awaiting line; a second acquisition unit configured to acquire frequencyof an object exiting the waiting line based on passage of the objectthrough a predetermined position; and an estimation unit configured toestimate waiting time in the waiting line based on the acquired numberof objects in the waiting line and the acquired frequency of an objectexiting the waiting line.
 2. The information processing apparatusaccording to claim 1, wherein the first acquisition unit acquires thenumber of objects included in the waiting line based on a number ofobjects having entered the waiting line and a number of objects havingexited the waiting line.
 3. The information processing apparatusaccording to claim 1, wherein the first acquisition unit acquires thenumber of objects in the waiting line by detecting objects from an imageobtained by photographing the waiting line and counting a number of thedetected objects.
 4. The information processing apparatus according toclaim 3, wherein the first acquisition unit acquires the number ofobjects in the waiting line by detecting objects from an area forcounting objects set in the image obtained by photographing the waitingline and counting the number of the detected objects.
 5. The informationprocessing apparatus according to claim 1, further comprising a firstaccepting unit configured to accept specification of an area forcounting objects through an area specification screen used for countingobjects, the area specification screen including an image obtained byphotographing the waiting line, wherein the first acquisition unitacquires a number of objects in the waiting line by detecting objectsfrom the area for counting objects indicated by the acceptedspecification within the image obtained by photographing the waitingline and by counting the number of the detected objects.
 6. Theinformation processing apparatus according to claim 1, wherein the firstacquisition unit acquires the number of objects in the waiting line at aset time by detecting objects from an image obtained by photographingthe waiting line at the set time and counting the number of the detectedobjects, and acquires the number of objects in the waiting line afterthe set time, based on the number of objects in the waiting line at theset time, a number of objects that have entered the waiting line sincethe set time, and a number of objects that have exited the waiting linesince the set time.
 7. The information processing apparatus according toclaim 1, wherein the first acquisition unit acquires the number ofobjects in the waiting line by detecting objects from a plurality ofimages of portions of the waiting line obtained by separatelyphotographing the portions at an identical time, counting the detectedobjects in the plurality of images, and summing together a result of thecounting.
 8. The information processing apparatus according to claim 1,wherein the first acquisition unit acquires the number of objects in thewaiting line by detecting portions where objects are set from an imageobtained by photographing the waiting line to detect objects and bycounting a number of the detected objects.
 9. The information processingapparatus according to claim 1, wherein the second acquisition unitacquires the frequency of an object exiting the waiting line based on anumber of objects passing through an exit of the waiting line within aset time period.
 10. The information processing apparatus according toclaim 9, wherein the second acquisition unit detects an object passingthrough the exit of the waiting line based on a plurality of imagesobtained by photographing the waiting line at set intervals within theset time period, and acquires the frequency of an object exiting thewaiting line based on a number of the detected objects.
 11. Theinformation processing apparatus according to claim 10, wherein thesecond acquisition unit detects an object that has passed through theexit of the waiting line based on positions of the object in theplurality of images obtained by photographing the waiting line at theset intervals within the set time period and acquires the frequency ofan object exiting the waiting line based on the number of the detectedobjects.
 12. The information processing apparatus according to claim 10,wherein the second acquisition unit detects an object that has passedthrough the exit of the waiting line based on a plurality of segmentsindicating a plurality of exits of the waiting line and positions of theobject in the plurality of images obtained by photographing the waitingline at the set intervals within the set time period and acquires thefrequency of an object exiting the waiting line based on the number ofthe detected objects.
 13. The information processing apparatus accordingto claim 11, wherein the second acquisition unit detects an object thathas passed through the exit of the waiting line based on a segmentindicating the exit of the waiting line and the positions of the objectin the plurality of images obtained by photographing the waiting line atthe set intervals within the set time period and acquires the frequencyof an object exiting the waiting line based on the number of thedetected objects.
 14. The information processing apparatus according toclaim 12, wherein the segment indicating the exit of the waiting line inthe plurality of images obtained by photographing the waiting line atthe set intervals within the set time period is set such that sizes ofareas surrounding the segment on both sides within the images aregreater than or equal to a set size.
 15. The information processingapparatus according to claim 12, further comprising a second acceptingunit configured to accept specification of the segment indicating theexit of the waiting line through a segment specification screen used tospecify a segment indicating the exit of the waiting line, the segmentspecification screen including an image obtained by photographing thewaiting line, wherein the second acquisition unit detects an object thathas passed through the exit of the waiting line based on the segmentindicating the exit of the waiting line specified by the acceptedspecification and the positions of the object in the plurality of imagesobtained by photographing the waiting line at the set intervals withinthe set time period and acquires the frequency of an object exiting thewaiting line based on the number of the detected objects.
 16. Theinformation processing apparatus according to claim 1, wherein thesecond acquisition unit acquires the frequency of an object exiting thewaiting line based on a number of objects passing through an exit of thewaiting line within a set time period and past frequency of an objectexiting the waiting line.
 17. The information processing apparatusaccording to claim 1, wherein the second acquisition unit acquires thefrequency of an object exiting the waiting line within each of set timeperiods based on a number of objects passing through an exit of thewaiting line within the set time period, and in a case where no objectexits from the waiting line within the time period, the secondacquisition unit acquires the frequency of an object exiting the waitingline based on a time period that has elapsed since latest exit of anobject from the waiting line and on a number of objects that have exitedfrom the waiting line within a time period including the time of thelatest exit of an object from the waiting line, out of the set timeperiods.
 18. The information processing apparatus according to claim 1,further comprising an output unit configured to output the estimatedwaiting time in the waiting line.
 19. The information processingapparatus according to claim 18, wherein the estimation unit estimatesthe waiting time in the waiting line every time an object enters orexits the waiting line, and wherein in a case where a time period fromwhen an object enters or exits the waiting line to when an objectsubsequently enters or exit the waiting line is greater than or equal toa threshold, the output unit outputs the estimated waiting time in thewaiting line in the next entrance or exit of the object.
 20. Aninformation processing method, the information processing methodcomprising: acquiring of the number of objects in a waiting line;acquiring frequency of an object exiting the waiting line based onpassage of the object through a predetermined position; and estimatingwaiting time in the waiting line based on the acquired number of objectsin the waiting line and the acquired frequency of an object exiting thewaiting line.
 21. A computer-readable storage medium storing a programfor causing a computer to a method, the method comprising: acquiring ofthe number of objects in a waiting line; acquiring frequency of anobject exiting the waiting line based on passage of the object through apredetermined position; and estimating waiting time in the waiting linebased on the acquired number of objects in the waiting line and theacquired frequency of an object exiting the waiting line.